2 feed black box to forecast hazard analysis critical control points
DESCRIPTION
The 2 double feeds black box is a modelling with 2 variables (human geography, physical geography) of the risk encountered. I have assumed for the presentation these risk were irrationalbehaviors. have presnted the with a mtrix risk portofolio and a combineeeTRANSCRIPT
GEO-HEALTH JOB
2 FEED BLACK BOX TO FORECAST HAZARD ANALYSIS CRITICAL CONTROL POINTS
GEO-HEALTH JOB
2 FEED BLACK BOX TO FORECAST HAZARD ANALYSIS CRITICAL CONTROL POINTS
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
forecast
real?
Can we make it ?
Yes we can !
How, when, where, who, what,...
x
T (event)
Recovery indicator
Curves of Disaster forecast reconciled with the organization environment to cope with tenses and the stress (psycological, brunts i.e wellbings,...assets, lives, properties of the hazardous event -tsunamy, earthquake,...)
No we cannot !
Time line
Number of affected people
T ?
ΔT : recovery leadtime
Graphs and the representation of the gap/risk
A FORECAST METHOD
© GS RADJOU, BIRD CEO
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
2 feed black box to forecast hazard analysis critical control points
BRUNTS (AFFECTION OR RECOVERIES) AND JOBS (LOSSES) DURING A DISASTER
Calendar (timeline)
Gross Domestic Product (GDP)
DISASTER
Average Gross Domestic Product
JAN. FEB. MAR. APR. MAY JUN.
HURRICANE SEASON IN USA (FLORIDA-GULF COAST)
JUI. DEC.
GDP
Real GDP
GDP
People affected or recoveringOr deads
job losses
JOBAffectation and leveling
Maximum GDPproduction
Job changes, less jobs, humanitaire jobs
Job returning to normal
Less GDP production
Maximum GDPproduction
Before the crisis During the crisis After the crisis
GDP min
GDP max
x
x
© GS RADJOU, BIRD CEO
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
2 feed black box to forecast hazard analysis critical control points
Psychological illness
Scale of the recovery
Maxi-
- - - -
++++
Brunts (Physical affectation)
important
weak
Survivor progress0
100
100
0
100
0
Recovery (R)
AFFECTED
Indicators
Risk source (losses of lives, losses of their family members, livelyhood and properties- insurance cannot return the wellbeing of survivors (as these are material assets- while survivors have lossed their psychological assets)
100
0
Survivor numbers
Method deterministic
Probabilitymethod
uncertainty
Recovery (R)
INDICATORS
© GS RADJOU, BIRD CEOInterdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia,
February 6- 8, 2013 – CEGeoIC_2013
2 feed black box to forecast hazard analysis critical control points
Parameters (*)(spatial, time)
Parameters (*)(spatial, time) Parameters (*)
(Survivors...)
Parameters (*)(Survivors...)
COSTGDPRESOURCESALLOCATIONSASSISTANCE….
1- VARIABLES (A,R)
2- ASSESSMENT3 STATUS(M,m,m)For any variables (parameters)
DATA INPUTS OUTPUTS
PROCESS 1PROCESS 1 PROCESS 2PROCESS 2
3- uncertainties(δ)
Uncertainties(δ)
BRUNTS (AFFECTION OR RECOVERIES) AND JOBS (LOSSES) DURING A DISASTER
Interdisciplinry CODATA Conference CEGeoIC, Boagota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO
(*) Encyclopedia of Geography: geography risk = physical geography + human geography
2 feed black box to forecast hazard analysis critical control points
33,33%
33,33%
33,33%
33,33% 33,33% 33,33%
AFFECTED
R E C O V E R Y(Survivors)
L E V E L S O F R I S K S(AND RISK EQUIPROBABILITY)
Affected Survivors (without brunts)
AffectedSurvivors
(100% With brunts- full
burnts)
Survivors 100%
No recovery/Survivor0%
Equipro-probability (P) for each/every scenario cases of survival (recovery) with various brunts/affectations case ~ P = 1/9 ≈ 0.11= 11,11.%
50% recovery
(Brunts) 50% Brunts
People neverrecovered, (life physical and Psychologicaldamages)
People lives affected people
(Physical recoveryNo mental recovery
People lives affected people
(mental recoveryNo physical recovery
People partially recovered
(but, no physical assets or
livelyhood)
People partially recovered
(but, no physical assets or
livelyhood)
People fully recovered
(but, no physical assets or
livelyhood)
Affected by tsunami(survivor with brunts
Affected by tsunami(survivor with brunts
Affected by tsunami(survivor with brunts
Affected by tsunami(survivor with brunts
Most AffectedBetween survivors of the tsunami first instant
Lucky survivors, they have been able to recover mentally and physically, but they have no houses, no food, assets livelyhood and properties
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO
2 feed black box to forecast hazard analysis critical control points
A1 R1A1 R1
A2 R1 A1 R1
A1 R3A1 R2
A3 R1
A2 R2
A3 R3
A2 R3
A3 R2
R1 R2 R3
A3
A2
A1
RISK MATRIX PORTOFOLIO
A REGION
A SITE
Risk class
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO
2 feed black box to forecast hazard analysis critical control points
AFFECTATION TABLE (DUAL GRAVITY TABLE
50% SURVIVORS-50% NTO SURVIVORS)
SURVIVORSMORE THAN
50% (Sufferers)
-People less affectedAnd
Recovering-
Intangibles-mental illness, psychological distress
People lives affectedby physical brunts
NOT SURVIVINGUNDER
50%(Sufferers)
-People more affected
and not recovering-
Survivors with bruntsPhysically
People lives affectedpsychological brunts
People lives affectedpsychological brunts
People affected likelyTo not survivePsychologicalillnesses
(R)
(A)
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO
2 feed black box to forecast hazard analysis critical control points
DETERMINISTIC
PROBABLISTIC
RISK CLASSES
RISK PORTOFOLIO MATRIX WITH A SCENARIO
© GS RADJOU, BIRD CEO
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
2 feed black box to forecast hazard analysis critical control points
bb
bb
gg
A1 R1 A2 R1 A3 R1 A1 R3 A2 R3 A3 R3
Bg
gB
gb
bg
A1 R2 A2 R2 A3 R2
gg
Bg
gB
BB
1 ½
½
¼¼¼¼
BB
bb
gg
gg
b: blueg: greyB: black
© GS RADJOU, BIRD CEO
HYBRID ORGANIZATIONS
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
Weight of an organization
Keys -codes-
Trend: survivorsTrend: not survivors
Probability p Probability P
P+p = 1 (99.99%) ≈100%
2 feed black box to forecast hazard analysis critical control points
RESOURCE PLANNING
NORMAL REFERENCE
CRISIS STARTS
DISASTER STARTS
EXPERIENCE (REAL) REFERENCE
(ASSUMED)
UNCERTAINTIES
Time
0 T1 T5 T3 T2 T4 T6
DATA IN DATA OUT
+ 50%
3 2 1
3 = not surviving0-25%2= likely to survive25%-50% people survived3= 50% -100% survivors
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013© GS RADJOU, BIRD CEO
2 feed black box to forecast hazard analysis critical control points
Can we make it better means ?
Can we reduce.....
Can we reduce the risk
Can we increase people resilience
Can we prevent the risk occurrence
Can we adapt the environment to hazards
Can we manage hazards
…...
Can we save....
Can we save people lives
Can we protect their assets
Can we protect their livelihoods
Can we protect their properties
….
Direct road map/action
Indirect road map/action
QUESTIONS / IMPROVMENT
actions expectations
Results/outputs =Conciliation between actions and expectations need to be materialized-
if not => there will be a gap or a failure causing increasing risks
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO
2 feed black box to forecast hazard analysis critical control points
2 feed black box to forecast hazard analysis critical control points
THANK YOU!
GEORGES RADJOU
Business Innovation Research Development
''BIRD''[email protected]
Www.facebook.com/gsradjouWww.slideshare.net/gsradjou
Interdisciplinary CODATA Conference CEGeoIC, Bogota, Colombia, February 6- 8, 2013 – CEGeoIC_2013
© GS RADJOU, BIRD CEO